Multilayer feedforward networks are universal approximators
Neural Networks
Neural networks and the bias/variance dilemma
Neural Computation
Shuffled complex evolution approach for effective and efficient global minimization
Journal of Optimization Theory and Applications
Comparative evaluation of genetic algorithm and backpropagation for training neural networks
Information Sciences—Informatics and Computer Science: An International Journal
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Multi-model data fusion for hydrological forecasting
Computers & Geosciences - Special issue on GeoComp 99- GeoComputation and the Geosciences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolving neural networks through augmenting topologies
Evolutionary Computation
Differential Evolution Training Algorithm for Feed-Forward Neural Networks
Neural Processing Letters
A Trigonometric Mutation Operation to Differential Evolution
Journal of Global Optimization
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Exploring dynamic self-adaptive populations in differential evolution
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Evolutionary product unit based neural networks for regression
Neural Networks
Neural Computing and Applications
Population size reduction for the differential evolution algorithm
Applied Intelligence
Expert Systems with Applications: An International Journal
Predicting software reliability with neural network ensembles
Expert Systems with Applications: An International Journal
Bio-inspired and gradient-based algorithms to train MLPs: The influence of diversity
Information Sciences: an International Journal
Super-fit control adaptation in memetic differential evolution frameworks
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Training feedforward neural networks using genetic algorithms
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Neural network ensembles: evaluation of aggregation algorithms
Artificial Intelligence
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Self-adaptive multimethod search for global optimization in real-parameter spaces
IEEE Transactions on Evolutionary Computation
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Differential evolution using a neighborhood-based mutation operator
IEEE Transactions on Evolutionary Computation
Efficient population utilization strategy for particle swarm optimizer
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Distributed differential evolution with explorative---exploitative population families
Genetic Programming and Evolvable Machines
Recent advances in differential evolution: a survey and experimental analysis
Artificial Intelligence Review
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Group search optimizer: an optimization algorithm inspired by animal searching behavior
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Lamarckian Hybrid of Differential Evolution and Conjugate Gradients for Neural Network Training
Neural Processing Letters
A differential evolution algorithm with self-adapting strategy and control parameters
Computers and Operations Research
A clustering-based differential evolution for global optimization
Applied Soft Computing
Differential evolution algorithm with ensemble of parameters and mutation strategies
Applied Soft Computing
An effective memetic differential evolution algorithm based on chaotic local search
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Adaptive strategy selection in differential evolution for numerical optimization: An empirical study
Information Sciences: an International Journal
A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization
Information Sciences: an International Journal
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Accelerating Differential Evolution Using an Adaptive Local Search
IEEE Transactions on Evolutionary Computation
Biogeography-Based Optimization
IEEE Transactions on Evolutionary Computation
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators
IEEE Transactions on Evolutionary Computation
Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Lung cancer cell identification based on artificial neural network ensembles
Artificial Intelligence in Medicine
A new evolutionary search strategy for global optimization of high-dimensional problems
Information Sciences: an International Journal
A note on teaching-learning-based optimization algorithm
Information Sciences: an International Journal
High-order and multilayer perceptron initialization
IEEE Transactions on Neural Networks
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
A constructive algorithm for training cooperative neural network ensembles
IEEE Transactions on Neural Networks
Using additive noise in back-propagation training
IEEE Transactions on Neural Networks
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
Adaptive population tuning scheme for differential evolution
Information Sciences: an International Journal
Information Sciences: an International Journal
Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia
Computers & Geosciences
Evolutionary artificial neural networks: a review
Artificial Intelligence Review
Optimization of self-organizing polynomial neural networks
Expert Systems with Applications: An International Journal
A survey on optimization metaheuristics
Information Sciences: an International Journal
International Journal of Remote Sensing
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
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Nature-inspired metaheuristics found various applications in different fields of science, including the problem of artificial neural networks (ANN) training. However, very versatile opinions regarding the performance of metaheuristics applied to ANN training may be found in the literature. Both nature-inspired metaheuristics and ANNs are widely applied to various geophysical and environmental problems. Among them the water temperature forecasting in a natural river, especially in colder climate zones where the seasonality plays important role, is of great importance, as water temperature has strong impact on aquatic life and chemistry. As the impact of possible future climate change on water temperature is not trivial, models are needed to allow projection of streamwater temperature based on simple hydro-meteorological variables. In this paper the detailed comparison of the performance of nature-inspired optimization methods and Levenberg-Marquardt (LM) algorithm in ANNs training is performed, based on the case study of water temperature forecasting in a natural stream, namely Biala Tarnowska river in southern Poland. Over 50 variants of 22 various metaheuristics, including a large number of Differential Evolution, as well as some Particle Swarm Optimization, Evolution Strategies, multialgorithms and Direct Search methods are compared with LM algorithm on ANN training for the described case study. The impact of population size and some control parameters of particular metaheuristics on the ANN training performance are verified. It is found that despite widely claimed large improvement in nature-inspired methods during last years, the vast majority of them are still outperformed by LM algorithm on the selected problem. The only methods that, based on this case study, seem competitive to LM algorithm in terms of the final performance (but not speed) are Differential Evolution algorithms that benefit from the concept of Global and Local neighborhood-based mutation operators. The streamwater forecasting performance of the neural networks is adequate, the major prediction errors are related to the river freezing and melting processes that occur during winter in the mountainous catchment under study.